As the ecosystem that Shibnobi is creating grows and gains traction, the challenges that this brings are increasing as well. The team, led by Cliff is pleased to make the following announcement to tackle these challenges and to set new standards:
Buyback and Burn
Within the DeFi world, token liquidity – which is what DEXs use to enable trading of tokens, have pools which are represented as a 50/50 split between the token itself and its pegged counterpart. I.e.: SHINJA is pegged to ETH.
The Shibnobi team intends to withdraw $4.2M ($2.1M in ETH, $2.1M in SHINJA) from the liquidity pool and subsequently perform a $2.1M ETH buyback over the next three weeks ($700K each week).
At the end of the three weeks, Shibnobi would then burn all these purchased tokens. As liquidity continues to grow, the team will continue to implement this type of buybacks to reduce supply, increase price, and stabilize the liquidity pool.
Missing Tokens Resolved
Shibnobi is also pleased to inform the investing public that the issue of missing tokens that occurred a few days after the buyback has been resolved. It was reported in the community that some tokens were missing in every wallet. Cliff and his team swung into action, identified the cause of the incident, and aimed to resolve the issue as quickly as possible.
The team assured all community members that they won’t lose any dollar value in their tokens: the percentage of the supply, market cap, and holder positions remain the same after the incident. To build trust and investors’ confidence, the team has increased reflection tax to 8% from 6% and conduct the remaining $1.4M buyback in small increments over a few days rather than $700K each week.
Shibnobi Software
Shibnobi introduces Shibnobi Software, a new division that will offer different software services, including auditing, consulting, and software development. The new service will help promote other projects at a cost that will be paid in $SHINJA.
Shibnobi Dojoswap
Shibnobi’s Dojoswap is a multi-chain swap platform designed to resolve the lack of user-friendly tools for Ethereum Virtual Machine compatible chains. It was developed by the Shibnobi team on a decentralized automated market maker protocol and uses liquidity pools that guarantee smooth blockchain transactions.
Dojoswap is compatible with popular blockchains like Ethereum, Polygon and Binance Smart Chain, but plans to expand this to additional EVM-compatible chains over the short to mid-term.
Dojoswap only permits the listing of tokens or projects on its protocol that have undergone a precheck, as well as KYC verification by Certik. Visit the official website and click on the apply button to begin listing your project.
DojoSwap Weekly Listing Report
Here is a weekly recap of the DojoSwap listing.
Wolverinu: An ERC-20 token that entered into crypto space in October 2021. This project has broken several records with over 14,000 holders in a short amount of time.
Grifters: Another innovative project whose team is working round the clock to promote, where it is based on the concept and belief that all innovative concepts, projects, and missions deserve a chance to thrive. The coins are imagined reality.
Piccolo Inu: A decentralized multi-purpose token that gives holders the leverage to mint custom NFT masterpieces. Holders can buy, sell, or trade NFTs for profits.
Lucky Shinu: A blockchain-powered gaming project, promising to hold contests for users with prizes such as cars, money, gadgets, vacations, and NFTs.
Streamer Inu: A community-based token that gives holders the opportunity to be a shareholder of the Streamers United LLC shares.
About Shibnobi
Shibnobi was launched in November 2021 by a team of experienced blockchain experts led by Cliff. Shibnobi is the world’s most deadly Shiba. It aims to refine the decentralized finance space and create different streams of passive income through a reflection mechanism for users and community members. Its native token, $Shinja, is deflationary and built on Kusari Blockchain.
The token operates through the POS consensus. $Shinja has been listed on different exchanges, including Uniswap, BitMart, Fegex, Lbank, HotBit, and ProBit.
As the European Union rushes to agree AI rules next month, Google’s chief legal officer Kent Walker said on Tuesday that regulations governing the use of AI should foster innovation. Walker’s remarks echoed those of a broad range of businesses and tech groups.
In an effort to reach a consensus by December 6, EU nations and legislators are currently ironing out the last details of a draft proposal by the European Commission.
A major problem is foundation models, like ChatGPT from OpenAI, which are AI systems trained on massive amounts of data and able to learn from fresh data to accomplish a range of tasks.
Walker said that rather than aiming for the first AI regulations, Europe should pursue the best ones.
“Technological leadership requires a balance between innovation and regulation. Not micromanaging progress, but holding actors responsible when they violate public trust,” he said in the text of a speech to be delivered at a European Business Summit.
“We’ve long said that AI is too important not to regulate, and too important not to regulate well. The race should be for the best AI regulations, not the first AI regulations.”
In order to build on current regulations and give businesses the confidence they need to continue investing in AI innovation, he called for proportionate, risk-based rules that make hard trade-offs between security and openness, data access and privacy, and explainability and accuracy.
The EU was forewarned last week by the business group DigitalEurope and 32 European digital associations not to overregulate foundation models.
With its ability to provide insights into consumer behavior, market trends, and operational efficiency, data analytics has developed into a vital tool for companies. The field of data analytics is about to take off, changing both businesses and industries. Let’s examine the major themes that will shape data analytics in the upcoming years in this post.
The Development of ML and AI
Data analytics is undergoing a revolution thanks to machine learning and artificial intelligence. AI and ML are used in a variety of industries, including healthcare and finance, because of their ability to handle enormous datasets, spot patterns, and make precise predictions. These technologies improve customer experiences, expedite processes, and improve decision-making. Data analytics will become more and more widespread as businesses use AI and ML for data analysis.
Taking Use of the Cloud’s Power
Data processing and storage have been revolutionized by cloud computing. Large datasets can now be accessed and stored by businesses from any location, making management and analysis simpler. Because of cloud computing’s scalability, businesses can process and analyze more data faster. As cloud computing becomes more and more common, data analytics’ potential keeps growing
Analytics for Real-Time Data
The field of data analytics is changing as a result of real-time analytics. Giving companies the ability to analyze data as it comes in gives them quick insights for quick decisions. Real-time analytics is particularly useful for detecting fraud and improving investment decisions in industries such as finance. The rapid advancement of data analytics is being driven by the broad use of real-time analytics technologies.
NLP, or natural language processing
The goal of the AI field of natural language processing, or NLP, is to make it possible for machines to comprehend human language. NLP explores unstructured data sources like emails, social media posts, and customer reviews in data analytics. By analyzing this data, important insights into the attitudes, tastes, and actions of customers are revealed. The scope of data analytics increases as more businesses use NLP for unstructured data analysis.
The Importance of Information Visualization
Data visualization becomes a powerful tool for effectively communicating insights and forecasts. A wider audience can access and comprehend data by using charts, graphs, and other visual representations. Using this method makes it easier to spot patterns and trends that might not be as obvious when looking at raw data. The increasing focus on data visualization is expected to expand the application of data analytics.
In conclusion, the significant growth of data analytics in the upcoming years is being driven by the convergence of trends like AI and ML, cloud computing, real-time analytics, NLP, and data visualization. Companies that adopt these technologies stand to benefit greatly. Those who want to work in data analytics should be aware of these trends as the field develops. Keep up with the most recent developments and set yourself up for success in this exciting and fulfilling industry.
Envision conversing with a computer that has the same natural flow and interest as a human. With the recent release of its human-like voice feature to all iOS and Android users, OpenAI’s ChatGPT has made that possible.
You can communicate with ChatGPT via text or voice thanks to this novel feature, which also increases its adaptability and user-friendliness. ChatGPT’s voice function adds a new level of interaction to any kind of communication, be it questioning, brainstorming, or just chit-chatting.
Why does this matter so much?
For a long time, scientists and science fiction authors have yearned to be able to have natural language conversations with computers. We’re getting closer to that dream than ever before with ChatGPT’s voice feature.
This discovery has a number of ramifications. For example, it could completely transform how we use technology, making it more user-friendly and available to people of all ages and backgrounds.
It might also create new opportunities in the areas of entertainment, customer service, and education.
How does it operate?
Advanced technologies such as natural language processing and text-to-speech synthesis power ChatGPT’s voice feature. The natural language processing system makes sure that the conversation flows naturally, and the text-to-speech engine turns ChatGPT’s text responses into speech that sounds natural.
What advantages does voice use offer?
The voice feature of ChatGPT has various advantages. It can, for starters, enhance naturalness and engagement in conversations. Additionally, it lets you communicate with ChatGPT hands-free, which is useful when you’re operating machinery or performing other tasks.
Additionally, those who struggle with typing or using a screen may find ChatGPT easier to use thanks to its voice feature. This applies to young children who are still learning to read and write as well as individuals with disabilities.
How to utilize the voice feature
It’s simple to use ChatGPT’s voice feature. Just launch the ChatGPT app, then press the headphone icon. After that, you’ll have a range of voices to choose from, including child, female, and male voices.
After choosing a voice, you can converse with ChatGPT in the same way as you would with a human. The chatbot will use a human-sounding voice to answer your voice commands and inquiries.
The voice feature of ChatGPT’s future
OpenAI is dedicated to advancing the voice feature of ChatGPT. The business intends to increase the number of voices, enhance the text-to-speech engine’s accuracy, and broaden the scope of voice-activated tasks that ChatGPT can perform.
With these improvements, ChatGPT has the potential to grow even further as a useful and powerful tool for learning and communication.